Julien Rebut

416 total citations
9 papers, 226 citations indexed

About

Julien Rebut is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Instrumentation. According to data from OpenAlex, Julien Rebut has authored 9 papers receiving a total of 226 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 5 papers in Automotive Engineering and 4 papers in Instrumentation. Recurrent topics in Julien Rebut's work include Autonomous Vehicle Technology and Safety (5 papers), Advanced Optical Sensing Technologies (4 papers) and Advanced Neural Network Applications (3 papers). Julien Rebut is often cited by papers focused on Autonomous Vehicle Technology and Safety (5 papers), Advanced Optical Sensing Technologies (4 papers) and Advanced Neural Network Applications (3 papers). Julien Rebut collaborates with scholars based in France and Canada. Julien Rebut's co-authors include Patrick Pérez, Alasdair Newson, Florence Tupin, Abdelaziz Bensrhair, Gwenaëlle Toulminet, Andrei Bursuc, Robert Laganière and Waqas Ahmed Malik and has published in prestigious journals such as SAE technical papers on CD-ROM/SAE technical paper series, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In The Last Decade

Julien Rebut

9 papers receiving 225 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Julien Rebut France	6	118	107	53	40	38	9	226
Michaël Meyer Germany	8	129 1.1×	133 1.2×	40 0.8×	23 0.6×	24 0.6×	16	255
Sihan Chen China	7	162 1.4×	146 1.4×	47 0.9×	35 0.9×	44 1.2×	16	298
Nicolas Scheiner Germany	6	155 1.3×	92 0.9×	45 0.8×	30 0.8×	49 1.3×	6	291
Paul Murcutt United Kingdom	4	198 1.7×	140 1.3×	59 1.1×	27 0.7×	52 1.4×	5	314
David J. Yoon Canada	10	208 1.8×	102 1.0×	34 0.6×	18 0.5×	51 1.3×	13	304
Ziyang Hong China	7	184 1.6×	96 0.9×	19 0.4×	37 0.9×	42 1.1×	24	282
Runwei Guan China	7	59 0.5×	60 0.6×	25 0.5×	34 0.8×	18 0.5×	27	202
Martin Holder Germany	9	121 1.0×	49 0.5×	101 1.9×	10 0.3×	40 1.1×	14	240
Julien Moras France	10	192 1.6×	155 1.4×	32 0.6×	74 1.9×	27 0.7×	28	303
Jorge Beltrán Spain	7	121 1.0×	129 1.2×	33 0.6×	18 0.5×	50 1.3×	14	238

Countries citing papers authored by Julien Rebut

Since Specialization

Citations

This map shows the geographic impact of Julien Rebut's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Julien Rebut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julien Rebut more than expected).

Fields of papers citing papers by Julien Rebut

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Julien Rebut. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Julien Rebut. The network helps show where Julien Rebut may publish in the future.

Co-authorship network of co-authors of Julien Rebut

This figure shows the co-authorship network connecting the top 25 collaborators of Julien Rebut. A scholar is included among the top collaborators of Julien Rebut based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Julien Rebut. Julien Rebut is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Rebut, Julien, et al.. (2022). Raw High-Definition Radar for Multi-Task Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 17000–17009. 65 indexed citations

2.

Newson, Alasdair, et al.. (2021). CARRADA Dataset: Camera and Automotive Radar with Range- Angle- Doppler Annotations. SPIRE - Sciences Po Institutional REpository. 5068–5075. 91 indexed citations

3.

Laganière, Robert, et al.. (2021). PolarNet: Accelerated Deep Open Space Segmentation using Automotive Radar in Polar Domain. 413–420. 1 indexed citations

4.

Laganière, Robert, et al.. (2021). PolarNet: Accelerated Deep Open Space Segmentation using Automotive Radar in Polar Domain. 413–420. 8 indexed citations

5.

Rebut, Julien, Andrei Bursuc, & Patrick Pérez. (2021). StyleLess layer: Improving robustness for real-world driving. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 8992–8999. 3 indexed citations

6.

Rebut, Julien, et al.. (2009). A monocular vision based advanced lighting automation system for driving assistance. 311–316. 15 indexed citations

7.

Rebut, Julien, et al.. (2006). OptiVeo: A Vision-Based Platform for Driving Assistance. SAE technical papers on CD-ROM/SAE technical paper series. 1. 2 indexed citations

8.

Rebut, Julien, Abdelaziz Bensrhair, & Gwenaëlle Toulminet. (2004). Image segmentation and pattern recognition for road marking analysis. 727–732 vol. 1. 28 indexed citations

9.

Rebut, Julien, Gwenaëlle Toulminet, & Abdelaziz Bensrhair. (2004). Road obstacles detection using a self-adaptive stereo vision sensor: a contribution to the ARCOS french project. 738–743. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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